| With the advancement and development of information technology,people's requirements for the network have gradually evolved to multi-protocol,multi-platform,and large-scale,which makes how to improve the quality and stability of the network become a research hotspot.A router acts as an intermediate hub for multiple network connections,and its performance directly affects the state of the network.Therefore,how to optimize and design the routing mechanism reasonably is of great significance for improving network quality and stability.This paper analyzes the principles,procedures,applications and advantages and disadvantages of the current simple genetic algorithm by studying a large amount of literature on network routing optimization methods and means at home and abroad,and proposes an improved genetic algorithm based on individual breeding strategy selection for these defects;The ant colony algorithm conducts detailed research and analysis,and summarizes the defects of the ant colony algorithm.Combining with the parallel ant colony algorithm that has been proposed by the predecessors,the design of Ad Hoc network Qo S routing optimization based on improved genetic ant colony coupling algorithm is proposed for the Ad Hoc Network(Qo S)Qo S(Quality of Serviee)routing optimization problem.Experiments are designed to verify the superiority of improved genetic ant colony coupling algorithm over single improved genetic algorithm,single improved ant colony algorithm,and traditional genetic ant colony coupling algorithm in Qo S routing optimization.The main contents include the following:(1)Study and comb the principles,processes and advantages and disadvantages of traditional genetic algorithms.The main drawback of genetic algorithms lies in the solution process.The algorithm selection strategy often uses roulette strategy,which is a probability problem,so it cannot be guaranteed.Every individual with high adaptability is retained to the next generation,and the problem of "premature maturity" will be introduced.To solve this problem,this paper proposes a genetic algorithm to improve the selection strategy.The core idea of ??this method is to use the number of individual reproductions to select,that is,for individuals,the number ofreproductions is positively related to the probability of being selected,so as to overcome the shortcomings of roulette selection and improve the search speed of the algorithm.Based on this,an improved genetic algorithm is designed to optimize the application of Qo S routing in Ad Hoc networks.Finally,the Network Simulator(NS)simulation results prove that the single improved genetic algorithm has a greater improvement than the traditional genetic algorithm in the number of iterations,solution success rate,end-to-end delay at different dwell times,and packet delivery rate.(2)A detailed study of the principle,mathematical model,advantages and disadvantages of the ant colony algorithm,on this basis,the improved ant colony algorithm is applied to the Ad Hoc network Qo S routing optimization application analysis,and experiments have confirmed that for large-scale Ad Hoc Network Qo S routing has obvious advantages in solving complex problems,which can effectively improve the convergence speed.Then,the detailed analysis and research on the coupling mechanism of genetic algorithm and ant colony algorithm.Through a lot of literature research,traditional genetic algorithm and ant colony algorithm have different efficiency in searching and solving.With time,genetic The algorithm and the ant colony algorithm have the opposite trends of convergence speed and solution speed.It is exactly using this point to couple the two,so that the advantages are complementary,and the shortcomings of the genetic algorithm and the ant colony algorithm can be eliminated.The central idea of this article is not to directly couple the two,but to couple the improved genetic algorithm with the improved ant colony algorithm(parallel ant colony algorithm)under the guidance of the above theoretical ideas,to further study the coupling strategy and mechanism,and design and improve the genetic ant colony Coupling algorithm in Ad Hod network Qo S routing optimization scheme,using NS tool to establish the mathematical model of genetic algorithm phase construction and ant colony phase construction in coupling algorithm,and gives the realization process and steps of the algorithm.(3)In view of the Ad Hoc network Qo S routing problem is a NP(Non-deterministic Polynomial Complete,NP-C)problem,the traditional routing algorithm is often not good,so this paper proposes to use an improved genetic ant colony coupling algorithm to solve Ad Hoc network Qo S routing problem.In order to prove the assumption in this paper,by establishing Ad Hoc network Qo S routing network model,building an experimental simulation platform,designing three sets of experiments to verify the optimization effect of the algorithm(improved genetic antcolony coupling algorithm)in Ad Hoc network Qo S routing.The simulation results show that comparing the single improved genetic algorithm,single improved ant colony algorithm,and traditional genetic ant colony coupling algorithm,the improved genetic ant colony coupling algorithm: 1)The number of solving iterations is reduced to 21.89,and the solution success rate is increased to 97.8.This shows that the algorithm has greater advantages in both the number of iterations and the success rate of the solution.2)The improved genetic ant colony coupling routing algorithm with different residence time has the lowest end-to-end delay and the highest packet delivery rate at different node movement speeds. |
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